We propose to study physiological mechanisms of neural selectivity that may underlie the perception of motion. We will make physiological measurements in area 17 & 18 of the cat, an animal whose motion mechanisms parallel those in the human, and also develop models that mimic motion responses. To study mechanisms we will use conventional stimuli generated on an oscilloscope, and also an array of optimally oriented, independently and randomly modulated bars, i,e., spatiotemporal "white noise". White noise provides rich cortical measurements, simultaneously in space and time, under a stable operating condition for comparison with conventional stimuli of lower duty-cycle. Another important feature of the stimulus is its complete representation of negative as well as positive response phases, because it's high average power increases a neuron's average firing rate. Our first Aim is to understand the basis for velocity selectivity in cortical cells by comparing moving-bar responses with predictions based on assembling the components of movements measured with white-noise. The assembly process is called convolution, and for quantitative comparisons with conventional measurements requires closely interleaving the two types of stimuli to prevent gain differences between the two different measures. A second Aim is to use the interleaved experiment to study the magnitude and temporal properties of the contrast-gain mechanism itself by manipulating the contrast power of the stimulus. Amplitude and shape of 1-bar white-noise responses provide these directly. Our third Aim is to develop a more precise description of motion-selective neurons, particularly simple cells. We will investigate modification of a motion-energy model to determine how directionally selective simple cells may carry both directional and phase information. Our fourth Aim is to understand selectivity for motion-in-depth. We will measure 2-bar interactions in each eye and between the eyes by using independent but simultaneous white-noise bar arrays in each eye. One-bar responses and 2-bar interactions will show differences in preferred velocity and point-to-point mapping in each eye that may be used to code 3D aspects of motion. These interactions will be convolved with stimuli moving along straight lines in depth to predict responses for examination of the dependence of 3D selectivity on linear and nonlinear mechanisms.